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Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs

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Outbound references

Observation 1b3f906c-a880-4325-93c5-cb9eeeab0041 · outbound

This paper cites Springer, New York, NY, USA (2006).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Springer, New York, NY, USA (2006)

Reference 1

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This paper cites Acta Numerica19, 451– 559 (2010) https://doi.org/10.1017/S0962492910000061.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Acta Numerica19, 451– 559 (2010) https://doi.org/10.1017/S0962492910000061

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This paper cites Journal of Basic Engineering82(1), 35–45 (1960) https://doi.org/10.1115/1.3662552 46.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal of Basic Engineering82(1), 35–45 (1960) https://doi.org/10.1115/1.3662552 46

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This paper cites The Journal of Chemical Physics21(6), 1087–1092 (1953) https://doi.org/10.1063/1.1699114.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs The Journal of Chemical Physics21(6), 1087–1092 (1953) https://doi.org/10.1063/1.1699114

Reference 4

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This paper cites Journal of Ocean Dynamics53, 343–367 (2003) https://doi.org/ 10.1007/s10236-003-0036-9.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal of Ocean Dynamics53, 343–367 (2003) https://doi.org/ 10.1007/s10236-003-0036-9

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This paper cites Quarterly Journal of the Royal Meteorological Society148(743), 620–640 (2021) https://doi.org/10.1002/qj.4221.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Quarterly Journal of the Royal Meteorological Society148(743), 620–640 (2021) https://doi.org/10.1002/qj.4221

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This paper cites American Journal of Mathematics60(4), 897–936 (1938).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs American Journal of Mathematics60(4), 897–936 (1938)

Reference 7

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This paper cites In: Pro- ceedings of the 9th International Conference on Neural Information Processing Systems.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs In: Pro- ceedings of the 9th International Conference on Neural Information Processing Systems

Reference 8

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This paper cites Current Science78(7), 808–817 (2000).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Current Science78(7), 808–817 (2000)

Reference 9

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This paper cites Math- ematics of Control, Signals and Systems2, 303–314 (1989) https://doi.org/10.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Math- ematics of Control, Signals and Systems2, 303–314 (1989) https://doi.org/10

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This paper cites Advances in Neural Information Processing Systems, 1097–1105 (2012) https://doi.org/10.1145/3065386.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Advances in Neural Information Processing Systems, 1097–1105 (2012) https://doi.org/10.1145/3065386

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This paper cites Foun- dations and Trends®in Machine Learning12(4), 307–392 (2019) https://doi.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Foun- dations and Trends®in Machine Learning12(4), 307–392 (2019) https://doi

Reference 12

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This paper cites Journal of Computational Physics378, 686–707 (2019) https://doi.org/10.1016/j.jcp.2018.10.045.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal of Computational Physics378, 686–707 (2019) https://doi.org/10.1016/j.jcp.2018.10.045

Reference 13

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This paper cites Jour- nal of Computational Physics463, 111301 (2022) https://doi.org/10.1016/j.jcp.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Jour- nal of Computational Physics463, 111301 (2022) https://doi.org/10.1016/j.jcp

Reference 14

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This paper cites Computer Methods in Applied Mechanics and Engineering415, 116229 (2023) https://doi.org/10.1016/j.cma.2023.116229 47.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Computer Methods in Applied Mechanics and Engineering415, 116229 (2023) https://doi.org/10.1016/j.cma.2023.116229 47

Reference 15

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This paper cites IEEE Transactions on Signal Processing70, 1532–1547 (2022) https://doi.org/ 10.1109/TSP.2022.3158588.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs IEEE Transactions on Signal Processing70, 1532–1547 (2022) https://doi.org/ 10.1109/TSP.2022.3158588

Reference 16

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Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal of Computational Physics477, 111918 (2023) https: //doi.org/10.1016/j.jcp.2023.111918

Reference 17

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This paper cites Springer Series in Computational Mathematics, vol.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Springer Series in Computational Mathematics, vol

Reference 18

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This paper cites Journal f¨ ur die reine und ange- wandte Mathematik1869(70), 105–120 (1869) https://doi.org/10.1515/crll.1869.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal f¨ ur die reine und ange- wandte Mathematik1869(70), 105–120 (1869) https://doi.org/10.1515/crll.1869

Reference 19

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This paper cites In: Glowinski, R., Golub, G.H., Meurant, G.A., Periaux, J.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs In: Glowinski, R., Golub, G.H., Meurant, G.A., Periaux, J

Reference 20

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This paper cites In: Chan, T.F., Glowinski, R., P´ eriaux, J., Widlund, O.B.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs In: Chan, T.F., Glowinski, R., P´ eriaux, J., Widlund, O.B

Reference 21

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This paper cites Mathematical and Computational Applications31(3) (2026) https://doi.org/10.3390/mca31030073.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Mathematical and Computational Applications31(3) (2026) https://doi.org/10.3390/mca31030073

Reference 22

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This paper cites Computer Methods in Applied Mechanics and Engineering354, 307–330 (2019) https://doi.org/10.1016/j.cma.2019.05.039.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Computer Methods in Applied Mechanics and Engineering354, 307–330 (2019) https://doi.org/10.1016/j.cma.2019.05.039

Reference 23

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This paper cites Physics of Fluids34(5), 055111 (2022) https://doi.org/10.1063/5.0088070.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Physics of Fluids34(5), 055111 (2022) https://doi.org/10.1063/5.0088070

Reference 24

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This paper cites IEEE Access8, 5283–5294 (2019) https://doi.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs IEEE Access8, 5283–5294 (2019) https://doi

Reference 25

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Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs In: Jianfeng, L., Rachel, W

Reference 26

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Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Adv Comput Math49, 1–39 (2023) https://doi.org/10.1007/ s10444-023-10065-9

Reference 27

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This paper cites CiCP28(5), 2002–2041 (2020) https://doi.org/10.4208/cicp.OA-2020-0164.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs CiCP28(5), 2002–2041 (2020) https://doi.org/10.4208/cicp.OA-2020-0164

Reference 28

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Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Computer Methods in Applied Mechanics and Engineering365, 113028 (2020) https://doi.org/10.1016/j.cma.2020.113028

Reference 29

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This paper cites Partitioned neural network approximation for partial differential equations enhanced with Lagrange multipliers and localized loss functions.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Partitioned neural network approximation for partial differential equations enhanced with Lagrange multipliers and localized loss functions

Reference 30

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This paper cites Computer Methods in Applied Mechanics and Engineering387, 114129 (2021) https://doi.org/10.1016/ j.cma.2021.114129.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Computer Methods in Applied Mechanics and Engineering387, 114129 (2021) https://doi.org/10.1016/ j.cma.2021.114129

Reference 31

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This paper cites Computers and Mathematics with Applications189, 109–128 (2025) https://doi.org/10.1016/j.camwa.2025.04.001.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Computers and Mathematics with Applications189, 109–128 (2025) https://doi.org/10.1016/j.camwa.2025.04.001

Reference 32

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Observation 5fe8af3b-54d9-4f47-9e45-f4259c433c36 · outbound

This paper cites In: 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), pp.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs In: 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), pp

Reference 33

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This paper cites Proceedings of the IEEE98(11), 1847–1864 (2010) https://doi.org/10.1109/JPROC.2010.2052531.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Proceedings of the IEEE98(11), 1847–1864 (2010) https://doi.org/10.1109/JPROC.2010.2052531

Reference 34

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This paper cites Computers and Chemical Engineering 156, 107544 (2022) https://doi.org/10.1016/j.compchemeng.2021.107544.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Computers and Chemical Engineering 156, 107544 (2022) https://doi.org/10.1016/j.compchemeng.2021.107544

Reference 35

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This paper cites Monthly Weather Review 49 139(7), 2046–2060 (2011) https://doi.org/10.1175/2011MWR3552.1.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Monthly Weather Review 49 139(7), 2046–2060 (2011) https://doi.org/10.1175/2011MWR3552.1

Reference 36

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This paper cites Journal of Computa- tional Science36, 100654 (2019) https://doi.org/10.1016/j.jocs.2019.100654.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal of Computa- tional Science36, 100654 (2019) https://doi.org/10.1016/j.jocs.2019.100654

Reference 37

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This paper cites Journal of Computational Physics509, 113059 (2024) https://doi.org/10.1016/j.jcp.2024.113059.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Journal of Computational Physics509, 113059 (2024) https://doi.org/10.1016/j.jcp.2024.113059

Reference 38

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Observation 438c28b8-e5a3-4520-b54e-a0400bca50d4 · outbound

This paper cites Signal Processing233, 110785 (2026) https://doi.org/10.1016/j.sigpro.2026.110785.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Signal Processing233, 110785 (2026) https://doi.org/10.1016/j.sigpro.2026.110785

Reference 39

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This paper cites Yale University Press, ??? (1923).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Yale University Press, ??? (1923)

Reference 40

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This paper cites Engineering Structures50, 179–196 (2013) https://doi.org/10.1016/j.engstruct.2012.12.029.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Engineering Structures50, 179–196 (2013) https://doi.org/10.1016/j.engstruct.2012.12.029

Reference 41

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Observation d6d7467e-261e-43a6-bd45-c0d31d9ef805 · outbound

This paper cites Cambridge University Press, ??? (2005).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Cambridge University Press, ??? (2005)

Reference 42

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This paper cites Advanced Modeling and Simulation in Engineering Sciences3(1), 24 (2016) https://doi.org/10.1186/ s40323-016-0075-7.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Advanced Modeling and Simulation in Engineering Sciences3(1), 24 (2016) https://doi.org/10.1186/ s40323-016-0075-7

Reference 43

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Observation 22e28958-9e26-46b7-a431-544e9168e39b · outbound

This paper cites Stochastic state estimation via incremental iterative sparse polynomial chaos based Bayesian-Gauss-Newton-Markov-Kalman filter.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Stochastic state estimation via incremental iterative sparse polynomial chaos based Bayesian-Gauss-Newton-Markov-Kalman filter

Reference 44

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Observation 1a8ac7be-32c8-4f7e-9009-cdd3a3caa8e4 · outbound

This paper cites In: Franzke, C.L.E., O’Kane, T.J.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs In: Franzke, C.L.E., O’Kane, T.J

Reference 45

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This paper cites IntechOpen, Rijeka (2013).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs IntechOpen, Rijeka (2013)

Reference 46

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Observation 53cb2c23-6a4d-4b39-b67d-69e8374da899 · outbound

This paper cites Recursive KalmanNet: Deep Learning-Augmented Kalman Filtering for State Estimation with Consistent Uncertainty Quantification.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Recursive KalmanNet: Deep Learning-Augmented Kalman Filtering for State Estimation with Consistent Uncertainty Quantification

Reference 47

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This paper cites 50 Journal of Machine Learning for Modeling and Computing1(2), 119–156 (2020) https://doi.org/10.1615/JMachLearnModelComput.2020035155.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs 50 Journal of Machine Learning for Modeling and Computing1(2), 119–156 (2020) https://doi.org/10.1615/JMachLearnModelComput.2020035155

Reference 48

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Observation 4a102189-a14a-4de1-9a14-d2b27455393d · outbound

This paper cites Foundations and Trends in Machine Learning3, 1–122 (2011) https://doi.org/ 10.1561/2200000016.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Foundations and Trends in Machine Learning3, 1–122 (2011) https://doi.org/ 10.1561/2200000016

Reference 49

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Observation ecbf0c7f-8ac7-4aba-8909-a832ab0b17a3 · outbound

This paper cites SIAM Journal on Scientific Computing16(5), 1190– 1208 (1995) https://doi.org/10.1137/0916069.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs SIAM Journal on Scientific Computing16(5), 1190– 1208 (1995) https://doi.org/10.1137/0916069

Reference 50

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This paper cites IF AC-PapersOnLine53(2), 8199–8204 (2020) https:// doi.org/10.1016/j.ifacol.2020.12.1996.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs IF AC-PapersOnLine53(2), 8199–8204 (2020) https:// doi.org/10.1016/j.ifacol.2020.12.1996

Reference 51

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Observation 925974b6-3321-461a-955a-e4e1e8c638f2 · outbound

This paper cites mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization

Reference 52

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Observation ad4c9fcb-aa98-4645-ae20-c5eaf5ca63fa · outbound

This paper cites Philosophical Transactions of the Royal Society A 210(459–470), 307–357 (1911) https://doi.org/10.1098/rsta.1911.0009.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Philosophical Transactions of the Royal Society A 210(459–470), 307–357 (1911) https://doi.org/10.1098/rsta.1911.0009

Reference 53

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Observation 5ff9d19a-80e1-44c5-817e-6c0b7333a1f3 · outbound

This paper cites Edge Computing in Low-Earth Orbit -- What Could Possibly Go Wrong?.

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Edge Computing in Low-Earth Orbit -- What Could Possibly Go Wrong?

Reference 54

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Observation 6a44ac82-4260-45db-b0c1-f75fddc411e5 · outbound

This paper cites Ansys, Inc., Canonsburg, PA (2024).

Domain-Decomposition Neural Surrogates for Scalable Decentralized Ensemble Kalman Filter Based Parameter Identification in High-Dimensional Stochastic PDEs Ansys, Inc., Canonsburg, PA (2024)

Reference 55

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